• DocumentCode
    3738848
  • Title

    Identification of weak buses for proper placement of reactive compensation through sensitivity analysis using a neural network surrogate model

  • Author

    Isaac Guevara;Marco Gutierrez;Pavel Zuniga

  • Author_Institution
    Analysis Department, CENALTE Puebla, M?xico
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The aim of this work is to present a surrogate model appropriate for carrying out sensitivity analysis studies. The surrogate model is obtained using a radial basis functions neural network. The study is based on the sensitivity of the overall power system bus voltage magnitudes to reactive power change. The objective is to locate a suitable power system bus for reactive compensation. To validate the proposed method, a power flow based sensitivity analysis is carried out in a power system in order to identify the most vulnerable bus. The findings can be used to identify buses where reactive power compensation can have the most impact. Simulation results are presented that confirms the validity of the proposal.
  • Keywords
    "Mathematical model","Computational modeling","Sensitivity analysis","Optimization","Power systems","Analytical models","Data models"
  • Publisher
    ieee
  • Conference_Titel
    Power, Electronics and Computing (ROPEC), 2015 IEEE International Autumn Meeting on
  • Type

    conf

  • DOI
    10.1109/ROPEC.2015.7395084
  • Filename
    7395084